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Record W6907763309 · doi:10.25384/sage.c.6271651.v1

KIdney aNd blooD prESsure ouTcomes in Childhood Cancer Survivors: Description of Clinical Research Protocol of the KINDEST-CCS Study

2022· other· en· W6907763309 on OpenAlexaffabout

Bibliographic record

VenueSage Journals Data · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoLondon Health Sciences CentreSickKids FoundationInstitute for Clinical Evaluative Sciences
Fundersnot available
KeywordsKidney diseaseKidney cancerCancerBlood pressureIncidence (geometry)Retrospective cohort studyCohort studyProspective cohort study

Abstract

fetched live from OpenAlex

Background:Approximately 30% of childhood cancer survivors (CCSs) will develop chronic kidney disease (CKD) or hypertension 15 to 20 years after treatment ends. The incidence of CKD and hypertension in the 5-year window after cancer therapy is unknown. Moreover, extent of monitoring of CCS with CKD and associated complications in current practice is underexplored. To inform the development of new and existing care guidelines for CCS, the epidemiology and monitoring of CKD and hypertension in the early period following cancer therapy warrants further investigation.Objective:To describe the design and methods of the KIdney aNd blooD prESsure ouTcomes in Childhood Cancer Survivors study, which aims to evaluate the burden of late kidney and blood pressure outcomes in the first ~10 years after cancer therapy, the extent of appropriate screening and complications monitoring for CKD and hypertension, and whether patient, disease/treatment, or system factors are associated with these outcomes.Design:Two distinct, but related studies; a prospective cohort study and a retrospective cohort study.Setting:Five Ontario pediatric oncology centers.Patients:The prospective study will involve 500 CCS at high risk for these late effects due to cancer therapy, and the retrospective study involves 5,000 CCS ≤ 18 years old treated for cancer between January 2008 and December 2020.Measurements:Chronic kidney disease is defined as Estimated glomerular filtration rate <90 mL/min/1.73 m2 or albumin-to-creatinine ratio ≥ 3mg/mmol. Hypertension is defined by 2017 American Academy of Pediatrics guidelines.Methods:Prospective study: we aim to investigate CKD and hypertension prevalence and the extent to which they persist at 3- and 5-year follow-up in CCS after cancer therapy. We will collect detailed biologic and clinical data, calculate CKD and hypertension prevalence, and progression at 3- and 5-years post-therapy. Retrospective study: we aim to investigate CKD and hypertension monitoring using administrative and health record data. We will also investigate the validity of CKD and hypertension administrative definitions in this population and the incidence of CKD and hypertension in the first ~10 years post-cancer therapy. We will investigate whether patient-, disease/treatment-, or system-specific factors modify these associations in both studies.Limitations:Results from the prospective study may not be generalizable to non-high-risk CCS. The retrospective study is susceptible to surveillance bias.Conclusions:Our team and knowledge translation plan is engaging patient partners, researchers, knowledge users, and policy group representatives. Our work will address international priorities to improve CCS health, provide the evidence of new disease burden and practice gaps to improve CCS guidelines, implement and test revised guidelines, plan trials to reduce CKD and hypertension, and improve long-term CCS health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.021
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.006
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0260.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.256
GPT teacher head0.500
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes2
Has abstractyes

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